Bringing together efficiency and effectiveness in distributed simulations: The experience with D-Mason

Agent-based simulation models are an increasingly popular tool for research and management in many fields. In executing such simulations “speed” is one of the most general and important issues because of the size and complexity of simulations. But another important issue is the effectiveness of the solution, which consists of how easily usable and portable the solutions are for the users, i.e. the programmers of the distributed simulation. Our study, then, is aimed at efficient and effective distribute simulations by adopting a framework-level approach, with our design and implementation of a framework, D-Mason, which is a parallel version of the Mason library for writing and running simulations of agent-based simulation models. In particular, besides the efficiency due to workload distribution with small overhead, D-Mason at a framework level proves itself effective since it enables the scientists that use the framework (domain expert but with limited knowledge of distributed programming) only minimally aware of the fact that the simulation is running on a distributed environment. Then, we present tests that compare D-Mason against Mason in order to assess the improved scalability and D-Mason capability to exploit heterogeneous distributed hardware. Our tests also show that several massive simulations that are impossible to execute on Mason (e.g. because of CPU and/or memory requirements) can be easily performed using D-Mason.

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